Technical Field
The present invention relates to an on-board apparatus, and in particular, to an on-board apparatus that predicts behavior of an own vehicle and performs processes based on prediction results.
Related Art
Conventionally, an on-board apparatus is known that predicts the course of an own vehicle based on yaw rate and steering angle. In addition, the on-board apparatus detects targets, such as pedestrians and other vehicles, using radar or a camera. For example, when a target is present on the predicted course of the own vehicle, the on-board apparatus issues a warning, intervenes in driving operations, and the like to avoid collision with the target.
An example of an apparatus such as this is an image recognition apparatus described in JP-A-2009-9209. The image recognition apparatus estimates a future positional relationship between the own vehicle and a target based on yaw rate, vehicle speed, and the like. Based on the estimated positional relationship, the image recognition apparatus estimates a future display area of the target in an image captured by a camera. The image recognition apparatus then performs image recognition on the display area, and performs enhanced display of the target or the like. The image recognition apparatus thereby issues a warning for collision avoidance while reducing processing load for target recognition.
In some instances, the yaw rate and the like significantly fluctuate instantaneously as a result of drifting of the steering wheel, noise, and the like. When the course is predicted based on yaw rate and the like, if such fluctuations are directly reflected in the course prediction, the accuracy of course prediction decreases. Appropriate driving assistance cannot be provided. Therefore, the above-described on-board apparatus is generally configured such as to perform a low-pass filter process on measurement values of the yaw rate and the like. As a result, the effects of sudden fluctuations in the yaw rate and the like can be suppressed. The course can be accurately predicted even when drifting of the steering wheel and the like occur.
However, when the low-pass filter process is performed, a time lag occurs until the changes in yaw rate and the like attributed to steering wheel operation are reflected in the course prediction. Therefore, for example, in situations where the curvature of the road suddenly changes, such as near an entrance to a curve, an accurate course prediction cannot be performed. A problem occurs in that appropriate driving assistance cannot be provided.